Principal Data Engineer

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This role is responsible for building end-to-end data products by understanding, ingesting, and curating data. Depending on the need, the product may be built on GCP or other platforms, with an understanding of Teradata and the Hadoop ecosystem. This role requires hands-on experience with SQL, Python, and Google Cloud native tools such as Google BigQuery, Dataflow, Cloud Composer, Pub/Sub, and Google Spanner. You will be....

Developing high-quality code that meets standards and delivers desired functionality using cutting-edge technology.

• Programming components, developing features, and frameworks.

• Working independently and contributing to immediate and cross-functional teams.

• Participating in design discussions and contributing to architectural decisions.

• Analyzing problem statements, breaking down problems, and providing solutions.

• Taking ownership of large tasks, delivering on time, and mentoring team members.

• Exploring alternate technologies and approaches to solve problems and following an agile-based approach to deliver data products.

• Six or more years of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training.

• Experience in data warehousing, Data Lakes, and big data platforms.

• Experience with GCP tools such as Cloud DataFlow, Cloud Shell SDK, Cloud Composer, Google Cloud Storage (GCS) and BigQuery

• Bachelor's or Master's degree in Computer Science, Information Science, Engineering, or a related field with 4+ years of relevant work experience.

• 4 or more years of proven experience collaborating with data engineers, architects, data scientists, and enterprise platform teams in designing and deploying data products and ML models in production

• 4 or years experience with GCP tools such as Cloud DataFlow, DataProc, Cloud Shell SDK, Cloud Composer, Google Cloud Storage (GCS), Cloud Functions and BigQuery

• Experience in designing and deploying Hadoop clusters and various big data analytical tools, including HDFS, PIG, Hive, Sqoop, Spark, and Oozie.

• Hands-on experience in designing and building data pipelines using Airflow, or Apache Beam in GCP (Dataproc and BigQuery) for ETL jobs.

• Hands-on experience implementing real-time solutions using Apache Beam SDK with Dataflow, Spark, or Flink as runners.

• Experience with real-time data streaming technologies such as Google Pub/Sub and Apache Kafka.

• Experience with advanced transformations and windowing functions in real-time data processing.

• Experience with Google Dataflow templates for creating reusable and scalable data processing pipelines.

• Experience working with at least one NoSQL database (HBase, Cassandra, Couchbase) and one relational database (Oracle, MySQL, Teradata).

• Strong problem-solving skills and the ability to empathize and maintain a positive attitude.

• Participation in technology and industry forums on evolving data engineering.

• Strategic thinker with the ability to apply a business mindset to data issues and initiatives, crafting cross-business strategies and plans for multiple stakeholders.

• Strong leadership, communication, persuasion, and teamwork skills.

• GCP/AWS Cloud certifications.

• Familiarity with Large Language Models and a passion for Generative AI tools.

If Verizon and this role sound like a fit for you, we encourage you to apply even if you don't meet every "even better" qualification listed above.

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